scholarly journals Specific and generic stem biomass and volume models of tree species in a West African tropical semi-deciduous forest

Silva Fennica ◽  
2016 ◽  
Vol 50 (2) ◽  
Author(s):  
Cedric Goussanou ◽  
Sabin Guendehou ◽  
Achille Assogbadjo ◽  
Maguette Kaire ◽  
Brice Sinsin ◽  
...  
2012 ◽  
Vol 74 (2) ◽  
pp. 77-88 ◽  
Author(s):  
GHS Guendehou ◽  
A Lehtonen ◽  
M Moudachirou ◽  
R Mäkipää ◽  
B Sinsin

2021 ◽  
Vol 13 (10) ◽  
pp. 1868
Author(s):  
Martina Deur ◽  
Mateo Gašparović ◽  
Ivan Balenović

Quality tree species information gathering is the basis for making proper decisions in forest management. By applying new technologies and remote sensing methods, very high resolution (VHR) satellite imagery can give sufficient spatial detail to achieve accurate species-level classification. In this study, the influence of pansharpening of the WorldView-3 (WV-3) satellite imagery on classification results of three main tree species (Quercus robur L., Carpinus betulus L., and Alnus glutinosa (L.) Geartn.) has been evaluated. In order to increase tree species classification accuracy, three different pansharpening algorithms (Bayes, RCS, and LMVM) have been conducted. The LMVM algorithm proved the most effective pansharpening technique. The pixel- and object-based classification were applied to three pansharpened imageries using a random forest (RF) algorithm. The results showed a very high overall accuracy (OA) for LMVM pansharpened imagery: 92% and 96% for tree species classification based on pixel- and object-based approach, respectively. As expected, the object-based exceeded the pixel-based approach (OA increased by 4%). The influence of fusion on classification results was analyzed as well. Overall classification accuracy was improved by the spatial resolution of pansharpened images (OA increased by 7% for pixel-based approach). Also, regardless of pixel- or object-based classification approaches, the influence of the use of pansharpening is highly beneficial to classifying complex, natural, and mixed deciduous forest areas.


IAWA Journal ◽  
2008 ◽  
Vol 29 (2) ◽  
pp. 189-207 ◽  
Author(s):  
Claudio S. Lisi ◽  
Mário Tomazello Fo ◽  
Paulo C. Botosso ◽  
Fidel A. Roig ◽  
Vivian R.B. Maria ◽  
...  

Many tropical tree species produce growth rings in response to seasonal environmental factors that influence the activity of the vascular cambium. We applied the following methods to analyze the annual nature of treering formation of 24 tree species from a seasonal semi-deciduous forest of southeast Brazil: describing wood anatomy and phenology, counting tree rings after cambium markings, and using permanent dendrometer bands. After 7 years of systematic observations and measurements, we found the following: the trees lost their leaves during the dry season and grew new leaves at the end of the same season; trunk increment dynamics corresponded to seasonal changes in precipitation, with higher increment (active period) during the rainy season (October–April) and lower increment (dormant period) during the dry season (May–September); the number of tree rings formed after injuries to the cambium coincided with the number of years since the extraction of the wood samples. As a result of these observations, it was concluded that most study trees formed one growth ring per year. This suggests that tree species from the seasonal semi-deciduous forests of Brazil have an annual cycle of wood formation. Therefore, these trees have potential for use in future studies of tree age and radial growth rates, as well as to infer ecological and regional climatic conditions. These future studies can provide important information for the management and conservation of these endangered forests.


2021 ◽  
Author(s):  
Talat Parveen ◽  
Orus Ilyas

Abstract The disturbance is a major factor driving the decline of tropical forests and their associated fauna. Henceforth, basic information on species diversity would be useful for assessing the success of management in the fragmented and human-disturbed landscape. We accounted for tree species diversity and their regeneration pattern from the tropical dry deciduous forest of Panna Tiger Reserve (PTR), India. Considering this, random vegetation sampling along with transects was carried out in different ranges of PTR. It is spread over in an area of 2998.98 km2 that situated in the northern part of Madhya Pradesh and distributed in Panna and Chhatarpur district. The tropical dry deciduous forest inventory in the 10.6132-ha area yielded a total of 46 woody species of > 10 cm GBH, belonged to 23 Families and 40 genera. The regeneration represented 27 species of < 30 cm height (seedling) under 16 families and 24 genera while sapling, which ranges from > 30cm to 1.3m, showed 24 species of 13 families and 32 genera. The Shannon diversity of Trees, seedlings, and saplings was 2.684, 2.525, and 2.401 respectively. A total stand density and basal area of 2391 stems of trees were estimated as 225.285 stand ha− 1 and 90.016 m2ha− 1 respectively. Tectona grandis scored the highest IVI value of 59.44 (19.81% of total IVI for all species) among the dominated tree species, followed by Acacia catechu (24.94), Abrus precatorius (23.25), Zizyphus xylopyra (22.94), Anogeissus latifolia (22.16) and Lagerstroemia parviflora (22.18). Nearly 23.913% of the total number of species was recorded as rare species. The highest seedling density was obtained for Diospyros melanoxylon followed by Zizyphus xylopyra, Aegle marmelos, Wrightia tintoria, and Tectona grandis, which declined in the subsequent sapling stage and showed a reverse pattern. Hence, the highest sapling density was recorded for Tectona grandis then Aegle marmelos, Wrightia tintoria, Diospyros melanoxylon, and Zizyphus xylopyra. A total of 36.956% of tree species were found to fail to establish in the community because species were represented by only adult or tree stage that listed as Not-regenerating. In terms of the most diverse family among the plant categories; viz. Tree, Seedling, Sapling, Fabaceae had the highest species richness. The highest tree stand density (127.576 stand ha− 1) was recorded in the girth class of 31-60cm (48.687% of the total tree stand density) followed by 10-30cm and 61-90cm. Likewise, a total basal area of 20.824 m2ha− 1 was occupied by 31-60cm that contributed 23.051% of the total basal area, so our data on the population structure of forest shows a similar trend wherein the distribution curve exponentially decreases with increasing girth classes that indicates not only a mid-successional forest but also a human-disturbed.


Author(s):  
Johannes Breidenbach ◽  
Lars T. Waser ◽  
Misganu Debella-Gilo ◽  
Johannes Schumacher ◽  
Johannes Rahlf ◽  
...  

Nation-wide Sentinel-2 mosaics were used with National Forest Inventory (NFI) plot data for modelling and subsequent mapping of spruce-, pine- and deciduous-dominated forest in Norway at a 16m×16m resolution. The accuracies of the best model ranged between 74% for spruce and 87% for deciduous forest. An overall accuracy of 90% was found on stand level using independent data from more than 42,000 stands. Errors mostly resulting from a forest mask reduced the model accuracies by approximately 10%. The produced map was subsequently used to generate model-assisted (MA) and post stratified (PS) estimates of species-specific forest area. At the national level, efficiencies of the estimates increased by 20% to 50% for MA and up to 90% for PS. Greater minimum numbers of observations constrained the use of PS. For MA estimates of municipalities, efficiencies improved by up to a factor of 8 but were sometimes also less than 1. PS estimates were always equally as or more precise than direct and MA estimates but were applicable in fewer municipalities. The tree species prediction map is part of the Norwegian forest resource map and is used, among others, to improve maps of other variables of interest such as timber volume and biomass.


2019 ◽  
Vol 11 (18) ◽  
pp. 2078 ◽  
Author(s):  
Yuhong He ◽  
Jian Yang ◽  
John Caspersen ◽  
Trevor Jones

Recent advances in remote sensing technology provide sufficient spatial detail to achieve species-level classification over large vegetative ecosystems. In deciduous-dominated forests, however, as tree species diversity and forest structural diversity increase, the frequency of spectral overlap between species also increases and our ability to classify tree species significantly decreases. This study proposes an operational workflow of individual tree-based species classification for a temperate, mixed deciduous forest using three-seasonal WorldView images, involving three steps of individual tree crown (ITC) delineation, non-forest gap elimination, and object-based classification. The process of species classification started with ITC delineation using the spectral angle segmentation algorithm, followed by object-based random forest classifications. A total of 672 trees was located along three triangular transects for training and validation. For single-season images, the late-spring, mid-summer, and early-fall images achieve the overall accuracies of 0.46, 0.42, and 0.35, respectively. Combining the spectral information of the early-spring, mid-summer, and early-fall images increases the overall accuracy of classification to 0.79. However, further adding the late-fall image to separate deciduous and coniferous trees as an extra step was not successful. Compared to traditional four-band (Blue, Green, Red, Near-Infrared) images, the four additional bands of WorldView images (i.e., Coastal, Yellow, Red Edge, and Near-Infrared2) contribute to the species classification greatly (OA: 0.79 vs. 0.53). This study gains insights into the contribution of the additional spectral bands and multi-seasonal images to distinguishing species with seemingly high degrees of spectral overlap.


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